Due to the large number of deaths and physical disabilities arising from diseases of the heart and major blood vessels in both adults and children, there exists a well-recognized need for reliable, accurate, and inexpensive blood flow measurement techniques. There are two general types of methods for measuring blood flow in humans--invasive and non-invasive techniques. Since the invasive methods involve radioactivity and injections, only one study is performed per patient, and this method is not suitable for utilization as a diagnostic screening technique. There are two types of non-invasive blood flow measurements: Doppler flow meter and plethysmography. The plethysmography method involves the compression of the neck veins and is of little practical use for diagnostic screening.
The Doppler method is the most commonly used non-invasive method for performing blood flow analysis and can be repeated as necessary. In general, this method involves the transmission of an ultrasound signal through the skin to a blood vessel and the detection of the Doppler shift in the reflected ultrasound signal resulting from the movement of the red blood cells. The Doppler shifted ultrasound signal is then utilized to determine the velocity of blood flow. The latter determination is complicated due to the presence of noise in the Doppler shifted signal, and because there are sets of blood cells moving at different velocities. Each of these sets of blood cells gives rise to a different frequency shift resulting in a Doppler shifted signal that is a complex wave. One example of noise that is present in the Doppler shifted signal is that due to the movement of blood vessel walls. The wall of a blood vessel moves out during the systole portion and returns during the distole portion of the cardiac cycle. These movements result in both low- and high-frequency noise components in the Doppler shifted signal.
Yet another problem that arises in attempting to determine the amount of blood flow from the Doppler shifted signals is that the heart rate varies not only from person to person, but within a given person over a relatively small number of cardiac cycles. This variation makes the interpretation of the resulting Doppler shifted signals difficult since the difference in cardiac cycles must be included if the blood flow information is to be extracted from the Doppler shifted signal since the resulting display from these signals can have a very different appearance.
Because of the complexity of the Doppler shifted signal, the presence of noise in the Doppler shifted signal, and the variation in cardiac cycles, it is necessary to perform analog or digital analysis of these signals in order to present the information in a manner which is useful to medical personnel attempting to diagnose blood flow rate. The copending application of C. M. P. Kierney, et al., discusses three major prior art techniques that are utilized to analyze these signals: zero crossing method, phase lock loop (PLL) method, and spectra analysis method utilizing Fourier analysis.
The Kierney application discloses the utilization of autoregressive analysis techniques for analyzing these signals. The method disclosed in Kierney is responsive to Doppler shifted signals and EKG signals for a plurality of cardiac cycles to precisely determine the start and the end of each cardiac cycle. The Doppler shifted signals for each cycle are then divided into a predetermined number of time segments or channels, and an autoregressive analysis is performed on each time channel. The result of this autoregressive analysis on each channel is a power spectrum for each channel of all cardiac cycles resulting in a large amount of data. These power spectra are then averaged on an individual channel basis over all cycles, and the result is presented on a color display with each color representing a particular power level at a given frequency and time segment.
The Kierney method presents to medical personnel an accurate and easy to diagnose display of the blood flow within a patient's blood vessel, and the method is superior to the prior art techniques. Kierney does require that a large number of power spectrum calculations be performed since these calculations are performed for every channel of every cardiac cycle. This results in a large number of calculations. In addition, after the power spectra are averaged over all channels and cycles, a large amount of data is still required to represent the results of the test. This data must either be immediately transferred to a hardcopy via a peripheral device or stored on secondary storage devices such as magnetic disk memories. In large clinical screening centers having access to large scale storage devices and a plurality of hard copy output devices, this large amount of data generated by the Kierney method does not present any particular problems. However, in small medical multiphase screening laboratories, the requirement of either having to immediately process and average data over a large number of cycles and plot the resulting power spectra on a hard copy device or to store all of the resulting power spectras requires computer power and peripheral devices not always available in those type of laboratories.
Therefore, there exists a need for a technique utilizing autoregressive analysis which does not require the calculation of the power spectra for each channel of every cycle and which results in a minimum amount of data so that the resulting data can be efficiently stored in computer data bases on a individual patient basis.